Business scope
Connect AI data center assessment, feasibility and solution architecture. Evaluate GPU capacity, inference performance, memory, power and cost with explicit evidence gates and a scoped post-quantum readiness workstream.
Roles and ownership
Data center operators, AI platform engineers, Infrastructure architects, Capacity and facilities planners, FinOps and investment teams, Enterprise risk reviewers participate within delegated responsibilities. Customer-authorized workload and configuration manifests, Accelerator and serving telemetry, Cluster inventory and facility energy records, Approved engineering and financial baselines retain the records they own.
Action and confirmation
Each connected action needs the relevant source identity, approved scope, current revision, receiving system, and permitted state transition. A sent request is distinct from an accepted business outcome. Unknown outcomes require reconciliation before a consequential retry.
Authority boundaries
The hosted toolkit review is read-only. Operational execution is a separate, customer-authorized activity with explicit scope and recovery criteria.
AGI describes the forward-looking infrastructure problem space. The delivered toolkit provides deterministic engineering assessment and planning.
Customer production telemetry, serving-engine integration, quality impact and realized savings must be established in the engagement. Toolkit validation does not establish fleet performance.
Facility controls, production cluster changes and ERP postings remain with the customer’s authorized systems and people.
Acceptance and measurement
Start with a free initial assessment. Scope one workload and infrastructure boundary, then define future-state requirements, evidence coverage, capacity/cost scenarios, feasibility gates and a conditional architecture. Add a post-quantum inventory and migration-plan review where relevant. Paid delivery follows a written proposal with pilot acceptance criteria.
- Accepted tasks per provisioned MW
- Cost and energy per accepted task
- Time to first token and inter-token latency
- Tail latency and quality acceptance
- GPU memory and KV-cache headroom
- Measured utilization and facility overhead
- Evidence coverage and recovery readiness
Deployment-specific decisions
The engagement confirms source systems, access purpose, field mappings, identity, operating volumes, retention, recovery, and support responsibilities. These decisions become part of the agreed implementation and acceptance record.